Beyond synchronization: The evolution of grid-following to grid-forming inverters and the quest for power system stability

Abdelwahab, Samir Ammar and Vokony, István (2026) Beyond synchronization: The evolution of grid-following to grid-forming inverters and the quest for power system stability. ENERGY REPORTS, 15. No. 109221. ISSN 2352-4847

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Abstract

The global integration of renewable energy is fundamentally reshaping power systems, replacing synchronous generators with inverter-based resources (IBRs). This transition introduces a critical stability challenge: conventional Grid-Following (GFL) inverters, which depend on a stable grid voltage for synchronization, become unstable in weak grids with low Short-Circuit Ratios (SCR). This paper provides a comprehensive review of the paradigm shift from GFL to Grid-Forming (GFM) inverters—the key to stabilizing future power systems. We analyze the core control architectures, operational limitations, and stability mechanisms of both paradigms, with a focused examination of synchronization instability in GFL units, including a precise small-signal impedance model explaining the negative incremental resistance effect and its impact on critical SCR thresholds in multiinverter systems. We further delve into the voltage-source behavior of GFM strategies like Droop Control and the Virtual Synchronous Machine (VSM), critically comparing their power sharing and frequency regulation capabilities in islanded microgrids and analyzing the stability trade-offs of virtual inertia in ultra-weak grids. The review covers advanced mitigation techniques, including adaptive control and virtual impedance, while also addressing their limitations in P-Q decoupling in resistive grids and exploring novel control paradigms. We provide a bifurcation analysis of large-signal instabilities, clarifying the role of current limiting strategies in catastrophic failures. Furthermore, we highlight the transformative role of Artificial Intelligence (AI) in enabling real-time, self-tuning inverters, and critically examine the optimal role of the AI layer (supervisory vs. direct control) and the attendant risks. Finally, we present a forward-looking research trajectory for developing an AIaugmented GFM inverter capable of stable operation in ultra-weak grids (SCR < 2), including the crucial development of Verification and Validation (V&V) frameworks for AI-based grid controllers to provide formal or probabilistic guarantees against adversarial data and cyber-physical attacks, providing a clear pathway to overcome the most pressing stability barriers in renewable-rich power networks.

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